Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks

Compressing large neural networks is an important step for their deployment in resource-constrained computational platforms. In this context, vector quantization is an appealing framework that expresses multiple parameters using a single code, and has recently achieved state-of-the-art network compression on a range of core vision and natural language processing tasks… Key to the success of vector quantization is deciding which parameter groups should be compressed together. Previous work has relied on heuristics that group the spatial dimension of individual convolutional […]

October 31, 2020 Python

Change Tick Frequency in Matplotlib

Introduction Matplotlib is one of the most widely used data visualization libraries in Python. Much of Matplotlib’s popularity comes from its customization options – you can tweak just about any element from its hierarchy of objects. In this tutorial, we’ll take a look at how to change the tick frequency in Matplotlib. We’ll do this on the figure-level as well as the axis-level. How to Change Tick Frequency in Matplotlib? Let’s start off with a simple plot. We’ll plot two […]

October 31, 2020 Python

How to Sort a Dictionary by Value in Python

Introduction A dictionary in Python is a collection of items that stores data as key-value pairs. In Python 3.7 and later versions, dictionaries are sorted by the order of item insertion. In earlier versions, they were unordered. Let’s have a look at how we can sort a dictionary on basis of the values they contain. Sort Dictionary Using a for Loop We can sort a dictionary with the help of a for loop. First, we use the sorted() function to […]

October 31, 2020 Banking, Big data, Business Analytics, Data Visualization, Intermediate, NLP, R, Technique, Text, Unstructured Data Leave a comment

Build a word cloud using text mining tools of R

This is how a word cloud of our entire website looks like! A word cloud is a graphical representation of frequently used words in a collection of text files. The height of each word in this picture is an indication of frequency of occurrence of the word in the entire text. By the end of this article, you will be able to make a word cloud using R on any given set of text files. Such diagrams are very useful when doing […]

October 31, 2020 Classification, Data Science, Intermediate, NLP, Python, Supervised, Technique, Text, Unstructured Data Leave a comment

6 Practices to enhance the performance of a Text Classification Model

Introduction A few months back, I was working on creating a sentiment classifier for Twitter data. After trying the common approaches, I was still struggling to get good accuracy on the results. Text classification problems and algorithms have been around for a while now. They are widely used for Email Spam Filtering by the likes of Google and Yahoo, for conducting sentiment analysis of twitter data and automatic news categorization in google alerts. However, while dealing with enormous amount of text […]

October 31, 2020 Intermediate, Libraries, Machine Learning, NLP, Programming, Python, Text, Unstructured Data Leave a comment

Extracting information from reports using Regular Expressions Library in Python

Introduction Many times it is necessary to extract key information from reports, articles, papers, etc. For example names of companies – prices from financial reports, names of judges – jurisdiction from court judgments, account numbers from customer complaints, etc. These extractions are part of Text Mining and are essential in converting unstructured data to a structured form which are later used for applying analytics/machine learning. Such entity extraction uses approaches like ‘lookup’, ‘rules’ and ‘statistical/machine learning’. In ‘lookup’ based approaches, […]

October 31, 2020 Advanced, Algorithm, Deep Learning, NLP, Python, Sequence Modeling, Supervised Leave a comment

Essentials of Deep Learning : Introduction to Long Short Term Memory

Introduction Sequence prediction problems have been around for a long time. They are considered as one of the hardest problems to solve in the data science industry. These include a wide range of problems; from predicting sales to finding patterns in stock markets’ data, from understanding movie plots to recognizing your way of speech, from language translations to predicting your next word on your iPhone’s keyboard. With the recent breakthroughs that have been happening in data science, it is found […]

October 31, 2020 Advanced, Algorithm, Business Analytics, Deep Learning, NLP Leave a comment

Replicating Human Memory Structures in Neural Networks to Create Precise NLU algorithms

Introduction Machine learning and Artificial Intelligence developments are happening at breakneck speed! At such pace, you need to understand the developments at multiple levels – you obviously need to understand the underlying tools and techniques, but you also need to develop an intuitive understanding of what is happening. By the end of this article, you will develop an intuitive understanding of RNNs, especially LSTM & GRU. Ready? Let’s go! Table of Contents Simple exercise – Tweet classification How does […]

October 31, 2020 Classification, Data Science, Intermediate, NLP, Project, Python, Supervised, Technique, Text, Unstructured Data Leave a comment

An NLP Approach to Mining Online Reviews using Topic Modeling (with Python codes)

Introduction E-commerce has revolutionized the way we shop. That phone you’ve been saving up to buy for months? It’s just a search and a few clicks away. Items are delivered within a matter of days (sometimes even the next day!). For online retailers, there are no constraints related to inventory management or space management They can sell as many different products as they want. Brick and mortar stores can keep only a limited number of products due to the finite space […]

October 31, 2020 Deep Learning, Intermediate, Libraries, NLP, Programming, Python, Text, Unstructured Data Leave a comment

Introduction to StanfordNLP: An Incredible State-of-the-Art NLP Library for 53 Languages (with Python code)

Introduction A common challenge I came across while learning Natural Language Processing (NLP) – can we build models for non-English languages? The answer has been no for quite a long time. Each language has its own grammatical patterns and linguistic nuances. And there just aren’t many datasets available in other languages. That’s where Stanford’s latest NLP library steps in – StanfordNLP. I could barely contain my excitement when I read the news last week. The authors claimed StanfordNLP could support more […]

« 1 … 736 737 738 739 740 … 906 »